AIMC Topic: Humans

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Transforming mental health research and care through artificial intelligence.

Science (New York, N.Y.)
Artificial intelligence (AI) holds transformative potential for the care of people with mental health illnesses. This Review explores key domains and emerging applications of AI in mental health, emphasizing the challenges that must be addressed to e...

Deep-learning analysis of 3D microarchitectural remodeling in hypertrophic cardiomyopathy.

Science (New York, N.Y.)
Hypertrophic cardiomyopathy (HCM), a genetic heart disease defined by unexplained cardiac wall thickening, is a leading cause of sudden death worldwide. However, the three-dimensional organization of cardiac tissue underlying left ventricular hypertr...

Leading large language models on a periodontology knowledge test.

Swiss dental journal
Large language models (LLMs) are increasingly used in clinical and educational settings. However, there is a paucity of data on LLMs' performance in specialized dental domains. This study assessed the performance of four LLMs, including two general-p...

A Review of Recent Developments in Artificial Intelligence and Big Data Technologies for Ophthalmology Referrals and Clinical Practice.

Medical science monitor : international medical journal of experimental and clinical research
Ophthalmology is undergoing rapid transformation through the integration of smart technologies such as artificial intelligence (AI), big data analytics, and clinical decision support systems (CDSS). With increasing pressure to improve clinical effici...

Explainable AI for pain perception: subject-independent EEG decoding using DeepSHAP and CNNs.

Biomedical physics & engineering express
Objective.Accurate classification of pain levels is essential for clinical monitoring, particularly in clinical populations with limited verbal communication. This study explores the feasibility of decoding pain from EEG using explainable deep learni...

ACFSENet: an adaptive cross-frequency global sparse encoding network for end-to-end EEG emotion recognition.

Biomedical physics & engineering express
End-to-end EEG-based emotion recognition is attracting increasing attention due to its potential in human-computer interaction, mental health, and affective brain-computer interfaces (aBCIs). However, most existing methods overlook cross-frequency in...

Harnessing AI in critical care: opportunities, challenges and key steps for success.

Thorax
BACKGROUND: The integration of artificial intelligence (AI) into critical care offers significant potential to enhance early diagnosis, predict patient deterioration, personalise treatment and inform clinical decision-making. Despite this promise, AI...

Genetic relationships between the gut microbiota and prostate cancer: Mendelian randomization combined with bioinformatics analysis.

The aging male : the official journal of the International Society for the Study of the Aging Male
BACKGROUND: Prostate cancer (PCa) is a leading cause of male cancer-related death globally. While the gut microbiota is linked to PCa, its genetic association remains unclear.

Machine learning and multi-omics integration identifies immunological predictors and mechanistic insights in autoimmune encephalitis.

Inflammation research : official journal of the European Histamine Research Society ... [et al.]
OBJECTIVE: To develop an interpretable prognostic prediction model for autoimmune encephalitis (AE) using immunological indicators and to investigate the potential role of nucleophosmin (NPM1) in disease pathogenesis through multi-omics approaches.

Dynamic Ensemble Selection for Early Detection of Deep Vein Thrombosis in Fracture Patients.

Journal of medical systems
Deep vein thrombosis (DVT) in fracture patients is often clinically silent, with a high incidence of thrombosis and associated mortality. Static machine learning methods struggle to address the challenge of early DVT diagnosis due to their inability ...